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  <div class="section" id="mindspore-ops-unsortedsegmentmax">
<h1>mindspore.ops.UnsortedSegmentMax<a class="headerlink" href="#mindspore-ops-unsortedsegmentmax" title="Permalink to this headline">¶</a></h1>
<dl class="class">
<dt id="mindspore.ops.UnsortedSegmentMax">
<em class="property">class </em><code class="sig-prename descclassname">mindspore.ops.</code><code class="sig-name descname">UnsortedSegmentMax</code><a class="reference internal" href="../../_modules/mindspore/ops/operations/array_ops.html#UnsortedSegmentMax"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#mindspore.ops.UnsortedSegmentMax" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes the maximum along segments of a tensor.</p>
<p>The following figure shows the calculation process of UnsortedSegmentMax:</p>
<img alt="api_python/ops/api_img/UnsortedSegmentMax.png" src="api_python/ops/api_img/UnsortedSegmentMax.png" />
<div class="math notranslate nohighlight">
\[\text { output }_i=\text{max}_{j \ldots} \text { data }[j \ldots]\]</div>
<p>where <span class="math notranslate nohighlight">\(max\)</span> over tuples <span class="math notranslate nohighlight">\(j...\)</span> such that <span class="math notranslate nohighlight">\(segment\_ids[j...] == i\)</span>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>If the segment_id i is absent in the segment_ids, then output[i] will be filled with
the minimum value of the input_x’s type.</p>
</div>
<dl class="simple">
<dt>Inputs:</dt><dd><ul class="simple">
<li><p><strong>input_x</strong> (Tensor) - The shape is <span class="math notranslate nohighlight">\((x_1, x_2, ..., x_R)\)</span>.
The data type must be float16, float32 or int32.</p></li>
<li><p><strong>segment_ids</strong> (Tensor) - A <cite>1-D</cite> tensor whose shape is <span class="math notranslate nohighlight">\((x_1)\)</span>, the value must be non-negative tensor.
The data type must be int32.</p></li>
<li><p><strong>num_segments</strong> (int) - The value specifies the number of distinct <cite>segment_ids</cite>.</p></li>
</ul>
</dd>
<dt>Outputs:</dt><dd><p>Tensor, set the number of <cite>num_segments</cite> as <cite>N</cite>, the shape is <span class="math notranslate nohighlight">\((N, x_2, ..., x_R)\)</span>.</p>
</dd>
</dl>
<dl class="field-list simple">
<dt class="field-odd">Raises</dt>
<dd class="field-odd"><ul class="simple">
<li><p><a class="reference external" href="https://docs.python.org/library/exceptions.html#TypeError" title="(in Python v3.8)"><strong>TypeError</strong></a> – If <cite>num_segments</cite> is not an int.</p></li>
<li><p><a class="reference external" href="https://docs.python.org/library/exceptions.html#ValueError" title="(in Python v3.8)"><strong>ValueError</strong></a> – If length of shape of <cite>segment_ids</cite> is not equal to 1.</p></li>
</ul>
</dd>
</dl>
<dl class="simple">
<dt>Supported Platforms:</dt><dd><p><code class="docutils literal notranslate"><span class="pre">Ascend</span></code> <code class="docutils literal notranslate"><span class="pre">GPU</span></code></p>
</dd>
</dl>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="c1"># case 1: Only have two num_segments, where is 0 and 1, and segment_ids=[0, 1, 1]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># num_segments = 2 indicates that there are two types of segment_id,</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># the first number &#39;0&#39; in [0, 1, 1] indicates input_x[0],</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># the second number &#39;1&#39; in [0, 1, 1] indicates input_x[1],</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># the third number &#39;1&#39; in [0, 1, 1] indicates input_x[2],</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># input_x[0], which is [1, 2, 3] will not be compared to other segment_id.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># Only the same segment_id will be compared.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">mindspore</span> <span class="kn">import</span> <span class="n">Tensor</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span> <span class="nn">mindspore</span> <span class="kn">import</span> <span class="n">ops</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">input_x</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">]])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">segment_ids</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">num_segments</span> <span class="o">=</span> <span class="mi">2</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">unsorted_segment_max</span> <span class="o">=</span> <span class="n">ops</span><span class="o">.</span><span class="n">UnsortedSegmentMax</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">output</span> <span class="o">=</span> <span class="n">unsorted_segment_max</span><span class="p">(</span><span class="n">input_x</span><span class="p">,</span> <span class="n">segment_ids</span><span class="p">,</span> <span class="n">num_segments</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">output</span><span class="p">)</span>
<span class="go">[[1. 2. 3.]</span>
<span class="go"> [4. 5. 6.]]</span>
<span class="go">&gt;&gt;&gt;</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># case 2: The segment_ids=[0, 0, 1, 1].</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># [1, 2, 3] will compare with [4, 2, 0],</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># and [4, 5, 6] will compare with [4, 2, 1].</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">input_x</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">]])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">segment_ids</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">num_segments</span> <span class="o">=</span> <span class="mi">2</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">unsorted_segment_max</span> <span class="o">=</span> <span class="n">ops</span><span class="o">.</span><span class="n">UnsortedSegmentMax</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">output</span> <span class="o">=</span> <span class="n">unsorted_segment_max</span><span class="p">(</span><span class="n">input_x</span><span class="p">,</span> <span class="n">segment_ids</span><span class="p">,</span> <span class="n">num_segments</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">input_x</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="go">    (4, 3)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">output</span><span class="p">)</span>
<span class="go">    [[4. 2. 3.]</span>
<span class="go">     [4. 5. 6.]]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># case 3: If the input_x have three dimensions even more, what will happen?</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># The shape of input_x is (2, 4, 3),</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># and the length of segment_ids should be the same as the first dimension of input_x.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># Because the segment_ids are different, input_x[0] will not be compared to input_x[1].</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">input_x</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">]],</span>
<span class="gp">... </span>                           <span class="p">[[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">1</span><span class="p">]]])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">segment_ids</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">num_segments</span> <span class="o">=</span> <span class="mi">2</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">unsorted_segment_max</span> <span class="o">=</span> <span class="n">ops</span><span class="o">.</span><span class="n">UnsortedSegmentMax</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">output</span> <span class="o">=</span> <span class="n">unsorted_segment_max</span><span class="p">(</span><span class="n">input_x</span><span class="p">,</span> <span class="n">segment_ids</span><span class="p">,</span> <span class="n">num_segments</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">input_x</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="go">    (2, 4, 3)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">output</span><span class="p">)</span>
<span class="go">    [[[1. 2. 3.]</span>
<span class="go">      [4. 2. 0.]</span>
<span class="go">      [4. 5. 6.]</span>
<span class="go">      [4. 2. 1.]]</span>
<span class="go">     [[1. 2. 3.]</span>
<span class="go">      [4. 2. 0.]</span>
<span class="go">      [4. 5. 6.]</span>
<span class="go">      [4. 2. 1.]]]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># case 4: It has the same input with the 3rd case.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># Because num_segments is equal to 2, there are two segment_ids, but currently only one 0 is used.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># the segment_id i is absent in the segment_ids, then output[i] will be filled with</span>
<span class="gp">&gt;&gt;&gt; </span><span class="c1"># the smallest possible value of the input_x&#39;s type.</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">segment_ids</span> <span class="o">=</span> <span class="n">Tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">))</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">output</span> <span class="o">=</span> <span class="n">unsorted_segment_max</span><span class="p">(</span><span class="n">input_x</span><span class="p">,</span> <span class="n">segment_ids</span><span class="p">,</span> <span class="n">num_segments</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">output</span><span class="p">)</span>
<span class="go">    [[[ 1.0000000e+00  2.0000000e+00  3.0000000e+00]</span>
<span class="go">      [ 4.0000000e+00  2.0000000e+00  0.0000000e+00]</span>
<span class="go">      [ 4.0000000e+00  5.0000000e+00  6.0000000e+00]</span>
<span class="go">      [ 4.0000000e+00  2.0000000e+00  1.0000000e+00]]</span>
<span class="go">     [[-3.4028235e+38 -3.4028235e+38 -3.4028235e+38]</span>
<span class="go">      [-3.4028235e+38 -3.4028235e+38 -3.4028235e+38]</span>
<span class="go">      [-3.4028235e+38 -3.4028235e+38 -3.4028235e+38]</span>
<span class="go">      [-3.4028235e+38 -3.4028235e+38 -3.4028235e+38]]]</span>
</pre></div>
</div>
</dd></dl>

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